The pTIF predicts how effective it would be to target specific biological factors for controlling the evolution of the individual patient’s neurodegenerative disease. Credit: Pixabay.
The Montreal Neurological Institute has created a novel approach to treatment neurodegenerative disorders, called a personalised therapeutic intervention fingerprint. Credit: Pixabay.
The pTIF predicts how effective it would be to target specific biological factors for controlling the evolution of the individual patient’s neurodegenerative disease. Credit: Pixabay.
The Montreal Neurological Institute has created a novel approach to treatment neurodegenerative disorders, called a personalised therapeutic intervention fingerprint. Credit: Pixabay.
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Personalised medicine has been in development for centuries, however, it has only become a major pharmaceutical industry trend in the past few years. It represents a shift away from a one- size -fits -all approach to treatments for particular conditions.
McGill University’s Montreal Neurological Institute has contributed to the development of personalised medicine by conducting a study that produced a so-called personalised Therapeutic Intervention Fingerprint (pTIF) using artificial intelligence and computational brain modelling techniques.
Lead author of the study Professor Yasser Iturria Medina explains: "A paper published around three years ago showed that the ten most sold drugs in the US are only helping between 4% and 25% of all the patients that are taking medicine. This is terrible.
"[However,] with a little research at the individual level, it could be identified who will respond [best to the drugs] because lots of them will have secondary effects. That was one of my main motivations."
He continues: "Personalised medicine has been used in cancer research, [but] it hasn’t happened in neuroscience. One of the main reasons is that usually in neuroscience there is a lot of separation between the different fields."
The pTIFs produced during the study relied on data from 331 Alzheimer’s patients who took part in the Alzheimer’s disease Neuroimaging Initiative trial and healthy controls. The data was available in multiple formats, including positron emission tomography and magnetic resonance imaging (MRI).
This new approach to personalised medicine works by predicting how effective it would be to target specific biological factors for controlling the evolution of the individual patient’s neurodegenerative disease. This makes it the first study to establish a direct link between brain dynamics and predicting a therapeutic response.
Understanding the pTIF as a form of personalised medicine
In creating the pTIF, the researchers were interested in characterising how different biological factors, such as muscular flow, amyeloid position and neurological activity interact and how interaction between these factors causes [neurological] degeneration in individual patients, Iturria Medina explains.
"We analyse them [these factors] using mathematical models.. to estimate how the variants interact in time and how the variants could vary from one to six comparing one brain region to other regions," he explains.
"We have a fingerprint system and identify equations that describes how the system works, and then we can also identify which will be the optimum system to control the system. We estimate using specific theories, such as quantum theories, which will be the optimum system to stop the neurodegeneration [in each individual patient]."
It is a series of quantitative indexes for how effective it would be target one or a combination of the biological factors, Iturria Medina explains. Since it focuses on the regional level within the brain, instead of getting one number for the brain, it provides numbers for specific biologic factors.
EEsentially, the pTIF is a ranking or a series of quantitative indexes for how effective it would be target one or a combination of the biological factors.
This categorises patients into sub-groups, which are verified by comparing the fingerprints to the patient’s genetic profiles. "If you take the ranking for different biological factors, this ranking is highly associated or predictive of the expression of a gene," Itu...
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